If you’re still hiring developers the way you did in 2024, you’re probably getting worse results for the same money.
After the layoffs and hiring freezes of the last couple of years, it looked like developers were abundant and companies could afford to be picky. For senior engineers, that assumption is out of date.
What Actually Happened in the Market
The contraction has eased, and companies need to ship again, not just cut costs. The hiring market didn’t return to 2023. It went somewhere different. Here’s what we think changed:
US developer supply tightened faster than demand. The layoffs also scared off early-career talent, so the junior pipeline is thinner, and senior developers who kept their jobs are pickier about where they go.
Offshore is the obvious way to widen the pool, but many companies that tried it regretted it or went hybrid. Canada is one place where cost efficiency and quality don’t pull in opposite directions, though it’s a smaller market.
The AI arms race changed the hiring profile. Gartner projects that 80% of the engineering workforce will need to upskill in AI-assisted development through 2027. Companies are increasingly hiring for “can write code.” They’re hiring for “can think critically about what code AI generates.” That’s a smaller pool. Your take-home assignment that an LLM can ace? It’s not screening for what you think it is.
The cost gap with Canada is still meaningful. US compensation stayed high while Canadian developer compensation moved more slowly, so nearshore still offers meaningful cost efficiency. Many Canadian candidates also want US-scale work.
Distributed work stuck. Companies forced remote during lockdowns kept much of that infrastructure. Teams that learned to work async-first have an easier time using nearshore talent than teams built around synchronous rituals. Whether they outperform office teams is contested, and we’d treat it as team-dependent.
Why Your Hiring Process Doesn’t Match Reality
If you’re still doing what worked two years ago, part of what looks like a supply shortage is a process mismatch.
Most companies are still hiring synchronously. Real-time interviews, whiteboard sessions, panel meetings, live coding challenges. You’re testing for the ability to think on your feet, handle pressure, communicate in the moment. Those are real skills, but for a distributed team the critical skill is the ability to think deeply and communicate that thinking clearly in writing. It’s reading someone else’s code without asking a live question. It’s joining an async code review, understanding context you didn’t write, and leaving feedback that forces clarity.
Your synchronous interview tests a different skill set. (A mix is reasonable: live conversation still tells you things writing doesn’t.)
The second problem: you’re still filtering on seniority and credentials as proxies for AI fluency. A developer with 10 years of Python experience didn’t automatically learn how to partner with LLMs. The developers who are thriving right now are the ones who’ve actively retrained.
The Decode Academy is our response to this gap. Candidates we place go through AI-led development modules. They cover LLM integration patterns, prompt engineering, how to evaluate AI-generated code. Companies get developers who’ve actively upskilled.
The third problem: you may be staffing for a team shape that’s changing. Some companies are running smaller teams augmented by AI. If you hire for a role that will look different in six months, expect boredom and turnover.
What This Changes in Practice
Quality is now about fit, not pedigree.
The “FAANG veteran” used to be a safe bet. Sometimes that pedigree now comes with resistance to async-first culture or skepticism of AI tools, and salary expectations you can’t match. Not always.
A developer who retrained in AI-augmented workflows and is hungry for a real opportunity can outperform the big-name hire. Hypothetically, at lower cost.
Time zone is leverage again, not a liability.
For five years, distributed hiring was defensive - “we can’t find talent locally, so we’ll go remote.” Now it’s more strategic. When you’re choosing a nearshore developer who operates in your timezone during US business hours, you’re not accepting a compromise on talent.
Cost efficiency is a feature again because quality improved.
Offshore arbitrage often fails on time zones, culture, and quality inconsistency. Nearshore addresses most of that: overlapping hours, similar work norms. The cost efficiency is meaningful, and it isn’t bought at the expense of quality.
Retention is the metric that matters.
Hiring speed was the flex for a while. “We filled the role in two weeks.” That’s not a win if the person leaves in eight months and you start over. Our 95% retention rate comes from optimizing for long-term fit over speed-to-placement. The tradeoff is a slower hire.
What This Means for Your Next Hire
One option: hire fewer developers, add nearshore talent, build async-first habits, invest in AI-fluency training, and put the savings into tooling and deep work. It won’t fit every team. If you need heavy in-person collaboration or deep domain specialists, you’ll still hire locally.
If you’re still running the 2024 playbook of synchronous interviews, seniority as a filter, and hiring for speed, start by changing one of the three. To talk it through, book a discovery call.
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